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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Free-Charge Carrier Generation in Homojunction Non-Polymeric Organic Semiconductor Films - The Role of the Optical Frequency Dielectric Constant

Engineering the dielectric constant (..epsilon..) to lower the exciton binding energy of the light-absorbing semiconductor can improve organic photovoltaic (OPV) device performance. Here, a series of materials are reported with 2-(3-oxo-2,3-dihydro-1H-inden-1-ylidene)malononitrile (INCN) acceptor end groups and a central glycolated bis(4H-cyclopenta[2,1-b:3,4-b']dithiophene) unit with large low-frequency (..epsilon..lf = 7.4-7.9 at 0.1-0.2 MHz) and optical-frequency (..epsilon..opt up to 6.6 at 2 x 1014 Hz) dielectric constants. The INCN end groups differed in whether they were protonated, chlorinated, or fluorinated, with the latter having the highest ..epsilon..opt. An ..epsilon..opt of 6.6 is predicted to lead to a low exciton binding energy of ~0.04 eV. Time-resolved microwave conductivity measurements showed a temperature-dependent yield-mobility product, with it increasing linearly from 340 K. The onset temperature was near that required to overcome the calculated exciton binding energy and indicates increased free charge generation in a homojunction film. Room temperature transient absorption spectroscopy revealed that photoexcitation rapidly converted to a lower energy state that was consistent with the formation of polarons or a charge transfer state. This work provides experimental evidence of the importance of ..epsilon..opt for the generation of free charges, and a strategy for development of efficient single chromophore homojunction OPV devices.

charge generation↗
DOE OSTI2024

Transport of penetrants in polymeric materials

Transport phenomena of chemical species in polymers underpin many applications. This mini-review discusses several key transport scenarios in polymer gels, melts and crosslinked polymer networks. Transport mechanisms of a wide variety of penetrant and polymer chemistries are discussed via activated hopping theory and cover across the rubbery, intermediate/deeply supercooled and glassy states of polymers. Moreover, we also discuss the ionic conductivity in polymer electrolytes, emphasizing the relationship between ion diffusion and the segmental relaxation of polymers and highlighting current challenges in the community. Finally, potential research directions are suggested concerning how external fields, such as mechanical force fields, active matter and self-propelling particles, affect the particle transport in polymers. This mini-review offers a general overview of motivations for studying penetrant transports in polymers and diverse mechanisms involved.

activated hopping↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Surface engineering of polymeric membranes with metal oxides for improved fouling resistance and superior oil-water separation

Rapid industrial growth has increased the need for efficient membranes to separate oil-water emulsions. Polyvinylidene fluoride (PVDF) membranes, although widely used due to their chemical inertness and favorable mechanical properties, suffer from fouling due to their intrinsic hydrophobicity. Modifying these membranes after fabrication offers a practical solution as it easily fits into existing large-scale manufacturing processes. Atomic layer deposition (ALD), an atomically-precise vapor phase surface modification technique, can create ultrathin metal oxide layers that greatly improve membrane hydrophilicity without significantly affecting the original pore size. However, PVDF's lack of reactive chemical moieties makes ALD challenging. Here, in this study, we present a simple alkali treatment that greatly enhances ALD nucleation and growth on PVDF membranes. This treatment imparts exceptional oil-water emulsion separation capabilities and antifouling behavior in PVDF membranes after just a few ALD cycles, surpassing the performance of PVDF membranes coated with hundreds of ALD cycles. This dramatic reduction in the number of ALD cycles required could enable cost-effective modification of commercial PVDF membranes at scale using spatial, roll-to-roll ALD. These modified membranes outperform reported modified PVDF membranes, with >99 % permeance recovery and <1 % irreversible loss of permeance and >98 % oil rejection from oil-water emulsions over 100 h continuous operation, making them promising for advanced water purification technologies.

Atomic layer deposition↗
DOE OSTI2025

Cyanine-Incorporated Amorphous Polymeric Carbon Dots for Optical Reactive Oxygen Species Sensing

Reactive oxygen species (ROS) are common cellular oxidants that when overproduced by cellular stressors cause harm to cells. Detection of ROS is of utmost importance to understanding a wide variety of cellular function and toxicity mechanisms. Conventional ROS fluorescence assays involve using a single dye to visualize the ROS quantity. Herein, we describe ROS-sensitive, fluorescent-dye-incorporated carbon dots with dual fluorescence capabilities and good biocompatibility. Carbon dots (CDs) made of citric acid and urea were synthesized with incorporated cyanine-3-amine (Cy3), a bright red fluorescent dye, to create Cy3-CDs. Additionally, to get Cy3 into the ROS-sensitive form, this work demonstrated that Cy3 alone and Cy3 within carbon dots can be electrochemically reduced to their colorless ROS-sensitive form. Cy3, CDs, and Cy3-CDs are all responsive to additions of superoxide, leading to an increase in the fluorescence. Overall, this work examines how O 2 •– and additional oxidizers interact with CDs, Cy3, and Cy3-CDs, and molecular-level hypotheses are explored that will inform the design of future carbon dot-based ROS sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Combined Machine Learning and Molecular Dynamics Reveal Two States of Hydration of a Single Functional Group of Cationic Polymeric Brushes

The state of hydration of a macromolecular system regulates a plethora of different properties of such a system. In this article, we develop a novel machine learning (ML) approach, based on the unsupervised clustering algorithm, for probing the hydration behavior of the {N(CH 3 ) 3 } + functional group of the PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] polyelectrolyte (PE) brush system. The PE brushes and the brush-supported water molecules and counterions (chloride ions) are first described using all-atom molecular dynamics (MD) simulations. The simulation data is subsequently used in our ML framework to identify that (1) the {N(CH 3 ) 3 } + functional groups of the PMETAC brushes have two distinct hydration states with one state (state 1) being characterized by less structured water molecules and the other state (state 2) being characterized by more structured water molecules and (2) an enhancement in the brush grafting density leads to the progressive dissapparenace of state 2. An increase in the grafting density increases the number of chloride counterions in a given volume around the {N(CH 3 ) 3 } + functional group and increases the number of shared water molecules between the {N(CH 3 ) 3 } + and Cl - . The chloride counterions are associated with a hydration layer with much less structured water molecules. Therefore, with an increase in the grafting density, an increase in the percentage of shared water molecules leads to the prevalence of the hydration state [of the {N(CH 3 ) 3 } + moiety] with less structured water molecules. Finally, we explain how the present findings are commensurate with two key previous related results, namely a significantly large chloride ion mobility inside the PMETAC brush layer and the {N(CH 3 ) 3 } + -Cl - average distance remaining independent of the PMETAC brush grafting density. Furthermore, we anticipate that the combined ML-MD-simulation approach proposed in this study can be adapted to probe other soft matter systems to reveal new insights of the underlying mechanisms of emergent phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗